基于层次格网索引的图幅接边处等高线高程错误识别和自动修正研究

等高线蕴含的历史高程信息可有效延长地形研究的时间序列,有利于深入挖掘地形变化长期规律,然而,图幅接边处的高程属性错误降低了等高线的数据质量,制约着等高线高程信息的实际应用。针对这一问题,该文提出一种基于层次格网索引的图幅接边处等高线高程错误识别和自动修正方法:首先,将层次格网索引与方向性二邻域算法相结合,以减少数据重复计算;然后,利用等高线空间位置标签及快速排序算法构建强空间位置关系,解决图幅接边处等高线匹配的准确性问题;最后,以高程冲突位点为驱动因子进行逻辑判断,实现等高线高程错误的识别及自动修正。实验结果表明:该方法运算效率较未进行效率优化时提高了203倍,接边处等高线高程错误识别与修正精度的最大值分别达97.71%和91.40%;相较于现有方法,该方法在精度和效率方面表现更佳,对区域性错误和变形等高线具有更高的适用性。     

Integrating multi-source big data to infer building functions

Information about the functions of urban buildings is helpful not only for developing a better understanding of how cities work, but also for establishing a basis for policy makers to evaluate and improve the effectiveness of urban planning. Despite these advantages, however, and perhaps simply due to a lack of available data, few academic studies to date have succeeded in integrating multi-source ‘big data’ to examine urban land use at the building level. Responding to this deficiency, this study integrated multi-source big data (WeChat users’ real-time location records, taxi GPS trajectories data, Points of Interest (POI) data, and building footprint data from high-resolution Quickbird images), and applied the proposed density-based method to infer the functions of urban buildings in Tianhe District, Guangzhou, China. The results of the study conformed to an overall detection rate of 72.22%. When results were verified against ground-truth investigation data, the accuracy rate remained above 65%. Two important conclusions can be drawn from our analysis: 1.The use of WeChat data delivers better inference results than those obtained using taxi data when used to identify residential buildings, offices, and urban villages. Conversely, shopping centers, hotels, and hospitals, were more easily identified using taxi data. 2. The use of integrated multi-source big data is more effective than single-source big data in revealing the relation between human dynamics and urban complexes at the building scale.     

Broad scale forest cover reconstruction from historical topographic maps

Land cover change is one of the major contributors to global change, but long-term, broad-scale, detailed and spatially explicit assessments of land cover change are largely missing, although the availability of historical maps in digital formats is increasing. The problem often lies in efficiency of analyses of historical maps for large areas. Our goal was to assess different methods to reconstruct land cover and land use from historical maps to identify a time-efficient and reliable method for broad-scale land cover change analysis. We compared two independent forest cover reconstruction methods: first, regular point sampling, and second, wall-to-wall mapping, and tested both methods for the Polish Carpathians (20,000 km²) for the 1860s, 1930s and 1970s. We compared the two methods in terms of their reliability for forest change analysis, relative to sampling error, point location and landscape context including local forest cover, area of the spatial reference unit and forest edge-to-core ratio. Our results showed that the point-based analysis overestimated forest cover in comparison to wall-to-wall mapping by 1–3%, depending on the mapping period. The reasons for the differences were mainly the backdating approach and map generalisation rather than the point grid position or sampling error. When we compared forest cover trajectories over time, we found that the point-based reconstruction captured forest cover dynamics with a comparable accuracy to the wall-to-wall mapping. More broadly, our assessment showed that historical maps can provide valuable data on long-term land cover trends, and that point-based sampling can be an efficient and accurate way to assess forest area and change trends. We suggest that our point-based approach could allow land cover mapping across much of Europe starting in the 1800s. Our findings are important because they suggest that land cover change, a key component of global change, can be assessed over large areas much further back in time than it is commonly done. This would allow to truly understand path dependencies, land use legacies, and historical drivers of land cover change.     

基于农户行为的耕地质量评价指标体系 构建的理论与方法

从农户土地利用目标变化相关理论出发, 依据在不同经济发展阶段下, 农户土地利用目 标的产量最大化、产量与利润最优化和利润最大化三个阶段的变化特征, 创建了基于农户土地利 用目标变化的“压力- 状态- 效应- 响应”逻辑框架模型; 并据不同经济发展阶段下的“压力- 状态- 效应- 响应”的变化特征, 构建了基于农户土地利用目标变化的耕地质量评价指标体系。这一评价 指标体系的建立为我国在不同经济发展阶段下, 从农户尺度上进行耕地质量保护提供政策依据。     

基于农户行为的耕地质量评价指标体系 构建的理论与方法

从农户土地利用目标变化相关理论出发, 依据在不同经济发展阶段下, 农户土地利用目 标的产量最大化、产量与利润最优化和利润最大化三个阶段的变化特征, 创建了基于农户土地利 用目标变化的“压力- 状态- 效应- 响应”逻辑框架模型; 并据不同经济发展阶段下的“压力- 状态- 效应- 响应”的变化特征, 构建了基于农户土地利用目标变化的耕地质量评价指标体系。这一评价 指标体系的建立为我国在不同经济发展阶段下, 从农户尺度上进行耕地质量保护提供政策依据。     

Incorporating spatial interaction patterns in classifying and understanding urban land use

Land use classification has benefited from the emerging big data, such as mobile phone records and taxi trajectories. Temporal activity variations derived from these data have been used to interpret and understand the land use of parcels from the perspective of social functions, complementing the outcome of traditional remote sensing methods. However, spatial interaction patterns between parcels, which could depict land uses from a perspective of connections, have rarely been examined and analysed. To leverage spatial interaction information contained in the above-mentioned massive data sets, we propose a novel unsupervised land use classification method with a new type of place signature. Based on the observation that spatial interaction patterns between places of two specific land uses are similar, the new place signature improves land use classification by trading off between aggregated temporal activity variations and detailed spatial interactions among places. The method is validated with a case study using taxi trip data from Shanghai.     

旅客机场选择行为意向的形成机制——以粤港澳大湾区为例

立足于旅客心理和行为认同,根据“推?拉?锚定”（PPM）理论,运用偏最小二乘法结构方程模型（PLS-SEM）,探讨机场选择行为意向的形成机制。研究结果表明,满意度、转移成本、感知票价、航班安排,以及机场服务质量的强制性流程、设施设备和环境等因素对机场选择行为意向有显著正向影响,替代者吸引力的负向影响虽然显著但作用微弱;航班安排、转移成本、强制性流程、设施设备和环境等因素影响程度随不同机场类型表现出明显差异,且主要显著存在于主要机场和辅助机场间、主要机场和其他机场间。因此,机场群高质量发展应注重对重复通航航班的协同运营,实现不同机场类型的航空资源互补化,优化主要机场的强制性流程服务,提升其他机场的设施设备和环境,促进航空服务的差异化和高品质化。     

A methodology with a distributed algorithm for large-scale trajectory distribution prediction

In this paper, we propose a method for predicting the distributions of people’s trajectories on the road network throughout a city. Specifically, we predict the number of people who will move from one area to another, their probable trajectories, and the corresponding likelihoods of those trajectories in the near future, such as within an hour. With this prediction, we will identify the hot road segments where potential traffic jams might occur and reveal the formation of those traffic jams. Accurate predictions of human trajectories at a city level in real time is challenging due to the uncertainty of people’s spatial and temporal mobility patterns, the complexity of a city level’s road network, and the scale of the data. To address these challenges, this paper proposes a method which includes several major components: (1) a model for predicting movements between neighboring areas, which combines both latent and explicit features that may influence the movements; (2) different methods to estimate corresponding flow trajectory distributions in the road network; (3) a MapReduce-based distributed algorithm to simulate large-scale trajectory distributions under real-time constraints. We conducted two case studies with taxi data collected from Beijing and New York City and systematically evaluated our method.     

陆地生态系统碳- 水耦合机制初探

陆地生态系统的碳循环和水循环是当前全球变化研究的热点。大量的研究已经表明两者之间具有密切的 耦合作用。但是目前对于两者的耦合关系和耦合机制还缺乏系统的分析和总结。本文在综合相关研究的基础上,对 陆地生态系统碳- 水耦合的基本过程和基本作用机制作了概括。我们认为陆地生态系统碳- 水耦合过程共包括土 壤- 植被节点、植被- 大气节点(气孔节点)、土壤- 大气节点和生化节点4 个碳- 水耦合节点。碳- 水间的生化反应、气 孔对光合- 蒸腾的共同控制和优化调控作用、生态系统对碳、水循环的同向驱动机制分别是陆地生态系统碳- 水耦 合的生物化学、生物物理学和生态学基础,共同构成了碳- 水耦合的基本作用机制。我们还用水分利用效率(WUE) 概念对碳- 水耦合过程中的碳/水耦合比例关系作了探讨。     

An agent-based model for optimal land allocation (AgentLA) with a contiguity constraint

Spatial optimization is complex because it usually involves numerous spatial factors and constraints. The optimization becomes more challenging if a large set of spatial data with fine resolutions are used. This article presents an agent-based model for optimal land allocation (AgentLA) by maximizing the total amount of land-use suitability and the compactness of patterns. The essence of the optimization is based on the collective efforts of agents for formulating the optimal patterns. A local and global search strategy is proposed to inform the agents to select the sites properly. Three sets of hypothetical data were first used to verify the optimization effects. AgentLA was then applied to the solution of the actual land allocation optimization problems in Panyu city in the Pearl River Delta. The study has demonstrated that the proposed method has better performance than the simulated annealing method for solving complex spatial optimization problems. Experiments also indicate that the proposed model can produce patterns that are very close to the global optimums.     

旅游集散地规划的地计算模型及案例

从地计算的角度出发,分析了地计算在旅游集散地规划中的问题,以江西上饶为例,运用可计算模型对旅游地域系统规划中的旅游中心集散地选择问题,旅游服务设施区位以及宾馆床位数的最优化问题进行了研究。这些问题的共同特征是它们是区域规划性质的、地理学的,而不是建筑学的景点景观设计。研究发现,地计算对于提高规划水平,是有效的,同时表明一般的空间分析问题,可以建立可计算模型。所有模型采用Visual Basic6.0(VB)编写程序实现计算,程序中调用了GIS软件中的MapObjects2.0控件实现地理显示、分析功能。这一工作显示VB与GIS软件结合,可以获取强大的空间分析功能。     

An efficient outlying trajectories mining approach based on relative distance

With a huge volume of trajectories being collected and stored in databases, more and more researchers try to discover outlying trajectories from trajectory databases. In this article, we propose a novel framework called relative distance-based trajectory outliers detection (RTOD). In RTOD, we first employed relative distances to measure the dissimilarity between trajectory segments, and then formally defined the outlying trajectories based on distance measures. In order to improve the time performance, we proposed an optimization method that employs R-tree and local feature correlation matrix to eliminate unrelated trajectory segments. Finally, we conducted extensive experiments to estimate the advantages of the proposed approach. The experimental results show that our proposed approach is more efficient and effective at identifying outlying trajectories than existing algorithms. Particularly, we analyzed the effect of each parameter in theory.     

基于微粒群优化算法的空间优化决策

空间优化决策是GIS应用中复杂而又常见的问题。由于涉及到大量的组合,使用穷举法等方法难以找到最优的解决方案,因此需要运用新的理论方法来解决这类问题。微粒群优化算法是近年来新兴的一种优化技术,与GIS相结合可解决空间优化决策问题。首先,对微粒群优化算法和空间优化决策问题作了简单介绍;然后,基于人口密度、最短距离约束条件下,通过GIS技术,对微粒群优化算法用于空间优化决策的方法、实施过程作了详细阐述;接着,用4×4方格单元对PSO方法的正确性、有效性进行了验证;最后,以广州市芳村区为例,对该方法进行实例验证。通过实验,证明微粒群优化算法具有较好的收敛速度、较高的结果精度,是解决空间优化决策问题的一种有效方法。     

基于分层分区法的中国历史耕地数据的网格化重建

网格化历史耕地数据集能为历史时期耕地变化研究提供更精确的支持,并且为全球环境气候变化研究模型模拟提供驱动数据。本文综合考虑了中国历代土地利用开发的特点及自然人文因子对耕地的影响,设计了一套对中国耕地先分区再分层分配的网格化方法。基于国内3个主流区域耕地数据研究成果,采用上述方法建立了1820年（清仁宗嘉庆二十五年）和1936年（民国二十五年）中国10 km×10 km分辨率的耕地数据集,并绘制了分布图。本文还利用国内具有代表性的区域数据集对重建结果进行对比验证。结果表明,该方法可以保证耕地数量的权威性,并且建立具有区域性的高精度历史耕地数据集。     

Vehicle trajectory modelling with consideration of distant neighbouring dependencies for destination prediction

Vehicle trajectory modelling is an essential foundation for urban intelligent services. In this paper, a novel method, Distant Neighbouring Dependencies (DND) model, has been proposed to transform vehicle trajectories into fixed-length vectors which are then applied to predict the final destination. This paper defines the problem of neighbouring and distant dependencies for the first time, and then puts forward a way to learn and memorize these two kinds of dependencies. Next, a destination prediction model is given based on the DND model. Finally, the proposed method is tested on real taxi trajectory datasets. Results show that our method can capture neighbouring and distant dependencies, and achieves a mean error of 1.08 km, which outperforms other existing models in destination prediction significantly.     

“一带一路”倡议下东北地区粮食产业转型升级路径

采用逻辑思辨的方法分析了“一带一路”倡议下东北地区粮食产业转型升级的重要价值与驱动，在“一带一路”倡议下东北地区粮食产业发展问题研判的基础上提出了其粮食产业转型升级的优化路径。主要结论如下：① 新结构经济学通过要素禀赋的内生驱动，产业梯度转移通过竞合效应与传导机制，顺向投资通过效率寻求型顺向投资、市场寻求型顺向投资和资源寻求型顺向投资，进出口贸易通过贸易自由化竞争效应、贸易结构先导效应、市场规模扩张效应共同驱动粮食产业优化升级；② 东北地区粮食产业发展面临粮食增长不稳定、增速不可持续性、种植结构需要继续优化以及种植质量和农产品效益亟需提升的问题；③ 未来东北地区需要以创新驱动为动力、以粮食产业链价值增值为着力点、以顺向投资为重要途径，以进出口贸易为突破口推动粮食产业转型升级。     

农村学校撤并后规模约束对学校优化布局的影响——以北京延庆区为例

在城镇化和农村人口减少的背景下,中国农村地区大量学校撤并,如何优化学校布局成为研究的重点。2008年原建设部发布了农村学校的最小和最大学生规模标准,但该标准对学校布局的影响尚缺乏研究。本文在包含最大距离约束的P-中值模型中增加了学校规模约束,构建了学校布局优化模型,并以北京延庆区小学布局为例,采用分支界定算法进行了求解。结果表明：实施学校规模标准化对学校优化选址有显著的影响,在优化模型中加入学校规模约束后,有65.22%的学校位置发生了改变,呈更加分散型布局;但在乡镇尺度下考察,学校的空间格局则基本未发生变化;学校规模标准化带来的距离增长较小,平均每个学生上学距离仅增长了135 m。并根据结果进一步讨论了研究结果对学校布局优化的政策启示。     

Ad hoc shared‐ride trip planning by mobile geosensor networks

Recent developments in miniaturization of computing devices, in location‐sensing technology and in ubiquitous short‐range wireless networks enable new types of social behaviour. This paper investigates one novel application of these technologies, ad hoc inner‐urban shared‐ride trip planning: Transportation clients such as pedestrians are seeking ad hoc shared rides from transportation hosts such as private automobiles, buses, taxi cabs or trains. While centralized trip planners are challenged by assigning clients and hosts in an ad hoc manner, in particular for non‐scheduled hosts, we consider the transportation network as a mobile geosensor network of agents that interact locally by short‐range communication and heuristic wayfinding strategies. This approach is not only fully scalable; we can also demonstrate that with short‐range communication, and hence, incomplete transportation network knowledge a system still can deliver near‐to‐optimal trips.     

基于共享单车轨迹的精细路网更新方法

城市道路数据的完整性和实时性是保障位置服务和规划导航路径的关键支撑。该文提出一种基于共享单车轨迹数据的新增自行车骑行道路自动检测和更新方法:首先,结合缓冲区方法和轨迹—路网几何特征检测增量轨迹;其次,基于分段—聚类—聚合策略提取更新路段,利用多特征融合密度聚类算法与最小外包矩形骨架线法提取增量道路中心线;最后,基于拓扑规则完成道路更新。以广州市共享单车轨迹为例,将该方法与传统栅格细化法进行实验对比,结果表明:该方法能有效更新道路网络,且在2 m和5 m精细尺度范围内提取的新增道路覆盖精度提升14%左右;在7 m尺度下精度达90%以上,在10 m尺度下精度达96%以上。     

基于手机信令大数据的机场腹地识别算法研究

机场腹地是完善和管控机场地表集疏运网络的基础依据,传统的机场腹地测算方法在时效性、准确性、解析性等方面已无法满足经济全球化时代事件管控和精准服务的需求。该文基于手机信令大数据构建新的机场腹地识别算法,并利用中国联通河北分公司提供的石家庄机场2019年10月2-8日的手机信令数据,识别石家庄机场腹地范围,通过测算不同尺度行政单元的进/出港旅客出行强度,揭示机场腹地内部结构的多尺度特征。研究发现:1)超过95%的出港旅客的出发地位于以机场为中心、200 km为半径的圆形区域内,或位于以机场为目的地的90 min等时圈内。2)市级尺度机场核心腹地为石家庄,主要腹地是保定,次要腹地是衡水、邢台、沧州和邯郸,6市进/出港旅客数量占比超过99%;县级尺度进/出港旅客的出行强度呈现圈层结构,且以机场为中心,向外逐步衰减;在乡级尺度,机场腹地不再连续,交通线附近出行强度高;村级尺度进/出港旅客出行密度呈现出城市>建制镇>村庄的特征。该算法为监测机场腹地的时空动态特征提供了工具,也为构建机场腹地的个性化扎根理论提供了支撑。